ERA-Interim is the latest global atmospheric reanalysis produced by the EuropeanCentre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF.

Within the Copernicus Climate Change Service (C3S), ECMWF is producing the ERA5 reanalysis which, once completed, will embody a detailed record of the global atmosphere, land surface and ocean waves from 1950 onwards. This new reanalysis replaces the ERA-Interim reanalysis (spanning 1979 onwards) which was started in 2006. ERA5 is based on the Integrated Forecasting System (IFS) Cy41r2 which was operational in 2016. ERA5 thus benefits from a decade of developments in model physics, core dynamics and data assimilation. In addition to a significantly enhanced horizontal resolution of 31 km, compared to 80 km for ERA-Interim, ERA5 has hourly output throughout, and an uncertainty estimate from an ensemble (3-hourly at half the horizontal resolution). This paper describes the general setup of ERA5, as well as a basic evaluation of characteristics and performance, with a focus on the dataset from 1979 onwards which is currently publicly available. Re-forecasts from ERA5 analyses show a gain of up to one day in skill with respect to ERA-Interim. Comparison with radiosonde and PILOT data prior to assimilation shows an improved fit for temperature, wind and humidity in the troposphere, but not the stratosphere. A comparison with independent buoy data shows a much improved fit for ocean wave height. The uncertainty estimate reflects the evolution of the observing systems used in ERA5. The enhanced temporal and spatial resolution allows for a detailed evolution of weather systems. For precipitation, global-mean correlation with monthly-mean GPCP data is increased from 67% This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

The COSMIC radio occultation mission represents a revolution in atmospheric sounding from space, with precise, accurate, and all-weather global observations useful for weather, climate, and space weather research and operations. GPS Signal GPS Satellite

SUMMARYA one-dimensional bending-angle observation operator for assimilating GPS radio occultation (RO) measurements has been integrated into the ECMWF four-dimensional variational assimilation (4D-Var) system. We have performed forecast impact experiments with 60 days of CHAMP RO measurements, in addition to the latest set of conventional and satellite data that are assimilated operationally, including radiances from the Atmospheric Infrared Sounder. It is demonstrated that the CHAMP measurements provide extremely good temperature information in the upper troposphere and lower stratosphere. In the southern hemisphere (SH), they produce a clear, statistically significant improvement in the r.m.s. forecast fit to radiosonde measurements over the day 1 to day 5 forecast range at 300, 200, 100 and 50 hPa. An improved r.m.s. fit to radiosondes is also evident at 100 hPa in the tropics. However, the observations degrade the 500 hPa geopotential height (500Z) field in the SH. This appears to be mainly caused by erroneous surface pressure increments in Antarctica. As a result, we have modified the GPS tangent-linear and adjoint routines, prior to the evaluation of the model-level pressures and geopotential heights, in order to remove the sensitivity of the model geopotential height values to the surface pressure. This improves the SH 500Z forecast scores, although a small degradation is still evident at the day 1 and day 2 forecast range.A simple method for estimating the degrees of freedom for signal (DFS) of a large variational assimilation system is noted and applied to estimate the DFS of the CHAMP measurements assimilated during a 12-hour assimilation window. The CHAMP measurements increase the total DFS of the 4D-Var system by ∼4%, and the DFS per CHAMP bending-angle profile is ∼34.

Forecasts (ECMWF) global reanalysis ERA-Interim. We find that GPSRO data present the highest daily assimilation percentage rate among all the various types of observations, suggesting that these data are readily usable by today's reanalysis systems. Over time, except when additional GPSRO data are introduced, the ERA-Interim short-term forecasts (background) are found to be stable compared with GPSRO data, and so are the ERA-Interim temperatures compared with radiosondes. This suggests that the GPSRO data are potentially as stable as the verification used here, at least to the extent that the possible quality variations in GPSRO data assimilated in ERA-Interim appear invisible when compared with radiosondes. We observe very good consistency between data from all six COSMIC receivers. Small differences between COSMIC and CHAMP (GRAS) data are observed in the lower troposphere (stratosphere). The mean effect of adding GPSRO data in ERA-Interim is to reduce temperature biases with respect to radiosondes in the ERA-Interim background by warming the tropopause region and lower stratosphere by about 0.1-0.2 K in all hemispheres. We also find hints of a drying effect in the mean water-vapour content in the Tropics in ERA-Interim when GPSRO data are introduced. The fit to upper tropospheric wind observations in the Southern Hemisphere and the Tropics is also improved when GPSRO data are present.